1. Field of the Invention
The present invention relates to image matching using a pattern matching method, and more specifically to an image matching apparatus, an image matching method, and an image matching program for matching fingerprint images, etc.
2. Description of the Related Art
When a specific object (an image of a person, a face, a combat car, etc.) is extracted from an image, and a matching operation is performed to check whether or not predetermined images (fingerprint images, face images, iris images, etc.) match, a image matching method that is called a pattern matching method is widely used. In the pattern matching method, the shapes of the characteristic portions and the similar portions in density distribution between a registered image (hereinafter referred to as an image T) and an image to be matched (hereinafter referred to as an image I) are obtained by a correlation arithmetic, etc., and it is evaluated whether or not the closest portions between them match each other. The pattern matching method can be applied to one-dimensional signal recognition such as voice recognition in addition to the two-dimensional signal recognition.
FIG. 1 shows the image matching method using the conventional pattern matching method.
The image matching method shown in FIG. 1 shows an example of a pattern matching method in which fingerprint images are matched.
As shown in FIG. 1A, an image T registered in advance is matched with an image I to be matched. To clarify the overlap between the two images the ridgeline of the image T is shown by a contour only.
As shown in FIG. 1B, the base of the pattern matching method in the image matching is performed by displacing the two images little by little until the position where the largest overlap between the images is obtained can be detected, and the overlap is evaluated.
For example, when the image matching method is used for fingerprint images as shown in FIGS. 1A and 1B, the image T is superposed on the image I, the image T is displaced in the x and y directions little by little until the position where the largest overlap is obtained between the image T and the image I can be detected. At the point where the largest overlap is obtained between the images, the overlap between the images is evaluated. The overlap can be evaluated by, for example, obtaining a product of the number of pixels of the overlapping pixels of the images, and evaluating the sum of the product values of all the overlapping portions. The evaluation value indicating the overlap is the higher when the overlap is the larger. Thus, in the image matching of fingerprint images, etc., when the evaluation value exceeds a predetermined value, it is determined in many cases that the images match.
For example, assuming that the image I is represented by I (x, y) and the image T is represented by T (x, y), the evaluation value V (x, y) for evaluation as to whether or not the images I and T match is expressed by the equation (1).v(x,y)=(1/Z)ΣI(i,j)T(i−x,j−y)  (1)
where Z indicates the area of the overlapping portions between I (i, j) and T (i, j).
In the equation (1) above, the values x and y when the evaluation value V (x, y) is the largest indicate the position where the image T is the closest to the image I, and the evaluation value V (x, y) at that time indicates the degree of overlapping between the image T and I.
When the images T and I are binary images, the above-mentioned T (x, y) and I (x, y) are 0 or 1. The evaluation value V (x, y) at this time can be obtained by the equation (1) above or the following equation (2).v(x,y)=(1/Z)Σnot(I(i,j)xorT(i−x,j−y))  (2)
where xor indicates an exclusive logical sum, and not indicates negation.
Thus, in the pattern matching method, the arithmetic expression used in a correlation arithmetic operation of image matching can be represented by various arithmetic expressions such as the equations (1) and (2) above, and the arithmetic algorithm is very simple. Therefore, it can be easily implemented on a computer, etc.
When the pattern matching method is applied in matching fingerprint images, and if a finger is dry or sweaty when the finger is pressed against the sensor for reading a fingerprint image, the ridgeline (line indicating the convex portion of a fingerprint) and a valley line (line indicating the concave portion of a fingerprint) can be broken or coupled. Additionally, when a finger is too strongly pressed, or a finger is moved while pressed to a sensor, the image input from the sensor can be fat or distorted. When an image is registered as an image to be matched with a broken or distorted portion included in the image, there occurs the problem of low accuracy for an arithmetic result of an evaluation value.
To solve the above-mentioned problem, for example, an image T and an image I are matched with each other using images of characteristic portions (images of the portions specific in the fingerprint images such as an endpoint indicating the tip point of a ridgeline, a delta indicating the portion from which a ridgeline, etc. is branched, etc., which are referred to as feature points) in the image data of registered fingerprints (for example, refer to the patent document 1 or 2). For example, feature points of an image T are recorded in advance, and an evaluation value for matching can be determined based on the ratio of the number of feature points of the image T to the number of feature points of the image I. Thus, by performing matching of fingerprint images using feature points, etc., the function of identifying each image can be improved. Therefore, the accuracy of evaluation can be enhanced although there is a distortion of a fingerprint image used in matching.
Patent Document 1                Japanese Patent Laid-open Publication No. Hei 6-195448 (pages 8˜10, FIGS. 7˜18)        
Patent Document 2                Japanese Patent Laid-open Publication No. Hei 2-245980 (pages 3˜6, FIGS. 1˜9)        
However, with an increasing number of small computers of late, small sensors are also required for image matching. Although the image matching is performed using feature points, etc., a small sensor provides a small space to which an image is read, and only a small number of feature points can be fetched for the smaller space, thereby causing the problem that sufficient accuracy cannot be obtained.
Furthermore, the conventional image matching method requires a very large number of arithmetic operations for obtaining an evaluation value V (x, y) because of iterative operations of:                1) displacing an image in parallel by one or more pixels; and        2) obtaining a sum of products on all pixels of overlapping portionsnormally as expressed by the equation (1) or (2) above. As shown in FIG. 2, in addition to displacing an image in parallel pixel by pixel, the amount of rotation can be considered. In this case, one image is rotated little by little while repeating the processes of 1) and 2), thereby further increasing the number of arithmetic operations. Thus, since the conventional image matching method requires a large number of arithmetic operations, it takes a long time to determine whether or not two images match.        
The present invention aims at providing an image matching apparatus, an image matching method, and an image matching program capable of shortening the time required to obtain a matching result with high accuracy.